The relationship between ambulatory arterial stiffness index and incident atrial fibrillation

Abstract Background The ambulatory arterial stiffness index (AASI) is an indirect measure of blood pressure variability and arterial stiffness which are atrial fibrillation (AF) risk factors. The relationship between AASI and AF development has not been previously investigated and was the primary aim of this study. Methods This was an observational cohort study of adults (aged 18–85 years) in sinus rhythm, who underwent 24‐h ambulatory blood pressure monitoring (ABPM) for the diagnosis of hypertension or its control. Results Eight hundred and twenty‐one patients (49% men) aged 58.7 ± 15.3 years were followed up for a median of 4.0 years (3317 patient‐years). In total, 75 patients (9.1%) developed ≥1 AF episode during follow‐up. The mean AASI was 0.46 ± 0.17 (median 0.46). AASI values (0.52 ± 0.16 vs. 0.45 ± 0.17; p < .001) and the proportion of AASI values above the median (65.3% vs. 48.4%; p = .005) were greater among the patients who developed AF versus those that did not respectively. AASI significantly correlated with age (r = .49; 95% confidence interval: 0.44–0.54: p < .001). On Kaplan–Meier analysis, higher baseline AASI by median, tertiles, and quartiles were all significantly associated with AF development (X 2: 10.13; p < .001). On Cox regression analyses, both a 1‐standard deviation increase and AASI > median were independent predictors of AF, but this relationship was no longer significant when age was included in the model. Conclusions AASI is an independent predictor of AF development. However, this relationship becomes insignificant after adjustment for age which is higher correlated with AASI.


| Twenty-four-hour ambulatory blood pressure and AASI measurement
All tests were done using an automatic ABPM device (Spacelab 90207, Spacelab Healthcare).An automated oscillometric cuff was placed on the nondominant arm.Blood pressure measurements were set to 30 min intervals throughout a 24-h recording period.The nighttime period was defined as the hours of 22:01 to 06:00 h and the daytime period as 06:01 to 22:00 h.Patients were only included if they had a minimum of 10 daytime and 5 nighttime ambulatory blood pressure measures during the 24 h recording period as previously described. 17,18Patients were advised not to use ABPM during periods of night shift work.The presence of sinus rhythm was confirmed on a 12-lead ECG or cardiac device check before the ABPM being performed.The AASI was calculated, as previously defined, 19 as 1-minus the regression slope of the diastolic to systolic blood pressure over the 24 h recording period.The full data for all the 24-h ABPMs were stored on TOMCAT (Philips CVIS Healthcare) reporting software.

| Blood tests
Venous blood for the measurement of full blood count and renal function were performed in local National Health Service laboratories.

| Outcome and AF diagnosis
The primary outcome was a diagnosis of AF.The diagnosis was based on AF confirmation on a 12-lead ECG or from ambulatory ECG or cardiac rhythm strip of >30 s duration.All patient health records were examined for the duration of follow up.Clinical information, including for the diagnosis of AF and confirmation of patient deaths, were obtained using the Dorset Primary Care and NHS Electronic Patient Records.

| Ethical approval
This study and its experimental protocol were approved by the Poole Hospital Clinical Research and Innovation Department and the West of Scotland Research Ethics Committee (REC reference: 20/WS/0097).As this was a registry cohort study the need for written informed consent was deemed not to be necessary by the ethics committee.

| Statistical analysis
Statistical analyses were performed with SPSS 26.0 (SPSS) and GraphPad Prism version 6.07 for Windows (GraphPad Software).
Identification of normality of continuous data was undertaken using data inspection and frequency histograms and the D'Agostino-Pearson normality test.Continuous data were presented as mean ± standard deviations (SDs) and median (interquartile range) for normally distributed and non-normally distributed data, respectively.Two group comparisons of continuous data were performed using an unpaired t test and Mann-Whitney U tests for normal and non-normally distributed data, respectively.Categorical data were examined using Fisher's exact tests and chi-squared tests with a relative risk (95% confidence intervals [CIs]) as appropriate.Correlations were examined using the Pearson and Spearman coefficients (95% CI) for normally and skewed data, respectively.We performed Kaplan-Meier time-to-events analyses to examine the risk of incident AF based on higher categorical AASI values based on the median, tertiles and AASI quartiles.The independent association between a 1-SD increase and higher (>median) AASI was undertaken using Cox regression with adjustment for patient age, sex, previous AF history, history of hypertension and 24-h diastolic blood pressure with results reported as hazard ratios (HR; 95% CI).Sensitivity analyses were also performed to assess the robustness of the final model by examining the influence of categorical age (>median vs. ≤median) and separately with only the inclusion of patients excluding without a history of previous AF.A two-sided p value of <.05 was considered significant for all comparisons.
T A B L E 1 Baseline demographics and clinical characteristics of the total cohort and patients with and without new-onset atrial fibrillation (AF).

| Sample size and power calculation
This was performed using a proprietary sample-size calculator (GraphPad StatMate version 2.00 for Windows).There have been previous studies that have examined the relationship between AASI using 24-h ABPM and AF.However, in previously published study Matsumoto et al examined 769 older adults and identified a significant relationship between 24-h (adjusted HR of 1.24 per 10 mmHg) and new-onset AF which affected 10.8% of their cohort (83/769). 20Our sample size of >769 patients was based on this publication and assuming a similar HR for AASI and incident AF.
Hypertension (63.8%) was the commonest cardiac risk factor with 51 (6.2%) patents identified as having a previous history of AF.

| Relationship between AASI and patient characteristics
There was an average of 27.1 ± 4.7 24-h ABPM readings per patient.

| Relationship between patient characteristics and AF
The median follow-up was 4.0 (range: 1-6.4) years.2).Nighttime systolic blood pressure was higher, and there was greater systolic, diastolic, and mean arterial blood pressure dipping among the AF versus non-AF patients.

| Outcome analyses
On Kaplan-Meier analysis higher categorical AASI based on median (>0.46), tertiles (<0.33 1st, 0.34-0.532nd, >0.53 3rd) and AASI quartiles (<0.35 1st, 0.34-0.462nd, 0.47-0.573rd, >0.574th) AASI were all associated with a significantly higher risk of incident AF (Figures 1 and 2).On Cox regression analyses, a 1-SD increase in AASI was a univariate predictor of future AF.On multivariate Cox regression analyses AASI (HR: 1.42; 95% CI: 1.11-1.82:p = .006),age, a previous history of AF, and male sex were independent predictors of incident AF (Table 3).However, following the inclusion of age into the model (along with sex, AF, history of hypertension, and diastolic blood pressure), the only independent predictors of AASI were age, male sex, previous AF, and no longer AASI (Table 3).Further Cox regression analyses using categorical AASI (above vs. ≤median) and similar covariate adjustments revealed similar results, with the independent prediction of higher AASI and AF being no longer significant after age (Table 3).
Sensitivity Cox regression analyses were performed to examine the effects of higher AASI based on tertiles and quartiles on the outcome of AF.This did not mitigate the neutralizing effect of age.We also examined the impact of only including the 770 patients without a previous AF history for a 1-SD increase in AASI and dichotomous AASI was similar with no significant and independent relationship between AASI and AF after age adjustment with the multivariable model.

| DISCUSSION
This is the first study to investigate the relationship between AASI measured, using 24-h ABPM, and AF.AASI was significantly higher among patients who subsequently developed AF versus those who remained in persistent sinus rhythm.On multivariable Cox regression analysis, increased and higher AASI were independent predictors of AF, but its significance was lost after adjustment for age, which was highly correlated with AASI.
AASI is emerging as a useful cardiovascular risk marker.
Although the manual calculation of AASI can take several minutes, automated AASI results are now provided as part of 24-h ABPM reporting software of several ABPM companies, including Spacelabs, used in this study.In our study, AASI was significantly higher among the patients who developed AF compared with those who did not.The strength of this relationship was enhanced given that the proportion of patients who developed AF was highest for each of the upper quantile, tertile, and quartile of AASI, with evidence of an ordinal effect.In a very recently published study of 8399 adults, it was shown that higher visit-to-visit systolic and diastolic blood pressure variability were both independently linked to incident AF. 14 In another recent study of 769 adults Matsumoto et al. also demonstrated a significant relationship between 24-h ABPM-derived systolic and diastolic blood pressure variability and incident AF.In their study, the adjusted RR for incident AF per each 1-SD increase in systolic blood pressure was 1.24 (95% CI: 1.11-1.37),and for diastolic blood pressure, was 1.30 (95% CI: 1.14-1.48).Furthermore, they observed that participants with the highest quartile of "both" systolic and diastolic blood pressure variability had the highest risk of incident AF, which is also supported by our data.AASI calculation itself reflects the linear relationship between diastolic and systolic blood pressure.Greater the variability in systolic blood pressure, diastolic blood pressure, or both would lead to a lower diastolic-systolic regression slope and a greater AASI given its calculation as 1-minus the diastolic-systolic blood pressure regression slope.
ABPM is generally considered to be the gold standard test for the diagnosis of hypertension and has been shown to be a stronger prognostic indicator of both future AF and cardiovascular events compared to home or office blood pressure. 21though AASI can be calculated using visit-to-visit blood pressure, its invention and prognostic value have been predominantly based using ABPM as used in our study.Moreover, unlike visit-to-visit blood pressure, ABPM addresses the influence of nocturnal blood pressure and its diastolic-to-systolic relationship and lessens the potential "white coat effects" of clinical visits on blood pressure indices.This is of major importance given that ABPM has been shown to be superior to both central and office blood pressure variability for AF prediction, supporting the premise for our study. 20 our study, we found that AASI was significantly higher amongst the patients with previous AF; this is a novel finding and strengthens our hypothesized AASI-AF relationship.It has wellestablished that previous AF is one of the strongest risk markers for future AF development which is enshrined in the 'AF-Begets AF' doctrine. 22Among the covariates examined, we noted that age, previous AF and male sex were the only variables that were independently associated with incident AF in our fully adjusted Cox regression model.Indeed, age and male sex are two of the most consistently represented AF risk factors used in well-validated AF prediction calculators. 23,24The consistency and scale of the mitigating effect of age on the AASI-AF relationship is interesting and raises the question as to whether age is in itself a confounder in the AASI This study has a number of limitations that need to be acknowledged.First, the sample size was modest but was powered based on a previous publication. 20With this sample size and 75 patients developing incident AF (9.1%) during our follow-up period, the number of independent variables that we could interrogate in our regression model was limited.Second, the definition of AF was based on its confirmed presence on a 12-lead ECG or cardiac rhythm strip conducted as part of routine clinical practice.Serial ECGs or ambulatory cardiac monitoring were not mandatory requirements for our study.Hence, the true incidence of new AF development post-ABPM monitoring is likely to be higher than that reported.However, this is unlikely to have altered our results and as the vast majority of AF events were clinically driven (worsening symptoms and/or hospitalization triggering the need for an ECG or cardiac monitor) and important.We did not adjust for ethnicity as >97% of our total cohort and all of the incident AF cases were Caucasian.Finally, we did not examine the relationship between AASI to AF-related adverse events (e.g., stroke, hospitalization, or heart failure), which is more clinically meaningful and will be the subject of future work.

| CONCLUSIONS
In summary, in this study, we examined the relationship between 24-h ABPM and incident AF.Both a 1-SD increase and higher AASI were significantly associated with incident AF.This association was independent of sex, diastolic blood pressure, hypertension history, and history of AF.However, its significance was lost after adjusting for age.Further, larger studies are required to explore the relationship between AASI and adverse AF-related clinical events.

F I G U R E 1
Kaplan-Meier graph showing AF event rate in patients with AASI above versus ≤median value of 0.46.AASI, ambulatory arterial stiffness index; AF, atrial fibrillation.

F
I G U R E 2 (A) Kaplan-Meier graph showing AF event rate in by AASI tertiles.(B) Kaplan-Meier graph showing AF event rate in by AASI quartiles.AASI, ambulatory arterial stiffness index; AF, atrial fibrillation.
Baseline demographics and 24-h ambulatory blood pressure readings of the full cohort and those with and without new-onset atrial fibrillation (AF).
During 3317 patients-years of follow-up, 75 patients (9.1%) developed one or T A B L E 2 Note: p values refer to the difference between the patients with and without AF development during follow-up.Abbreviation: ABPM, ambulatory blood pressure monitor.moreepisodes of AF.AF patients were older, had greater body mass, were more likely to have a history of hypertension, diabetes mellitus, previous stroke, or heart failure compared with those without AF development (Table1).Patients who developed AF were more likely to be treated with a beta-blocker, diuretic, or alpha-blocker and had a lower baseline estimated glomerular filtration rate and left ventricular ejection fraction.3.4 | AASI, ambulatory blood pressure, and AF 25A B L E 3 Relationship between AASI and covariates to Incident atrial fibrillation (AF) development.relationship.Age has been consistently shown to strongly correlate with AASI, and this relationship was again supported by our data.Age is also strongly correlated and causally related to AF development.25Thismakes the interpretation of our age-adjusted Cox-multivariable regression model quite challenging.It would appear that AASI acts as a mediator in the causal pathways between age and AF.The strong influence of age in the AASI-AF relationship persisted even with the use of age as categorical variable and also the inclusion of only AF naïve patients.
Note:In model 1, the covariate adjustments were sex, history of hypertension, previous AF, AASI, and diastolic blood pressure; model 2 included model 1 plus additional adjustment for age.